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researcher

J. Sacramento

21 papers hereh-index 223.6k citations47 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author8
  • last author7

Across the 18 of 21 papers where every author was matched, so the position is known.

fields
  • cs.LG14
  • q-bio.NC6
  • cs.NE1

identity via Semantic Scholar / OpenAlex

activity
20122023
most citedTransformers learn in-context by gradient descent

89 citations · 328 across the 17 of their papers we have counts for

collaborators
Showing 2020Show all

3 papers · 1 filter

cs.LG2020

Neural networks with late-phase weights

Johannes von Oswald, Seijin Kobayashi, Alexander Meulemans +3

The largely successful method of training neural networks is to learn their weights using some variant of stochastic gradient descent (SGD). Here, we show that the solutions found…

q-bio.NC2020

Conductance-based dendrites perform reliability-weighted opinion pooling

Jakob Jordan, João Sacramento, Mihai A. Petrovici +1

Cue integration, the combination of different sources of information to reduce uncertainty, is a fundamental computational principle of brain function. Starting from a normative mo…

cs.LG2020★ 32 cited

A Theoretical Framework for Target Propagation

Alexander Meulemans, Francesco S. Carzaniga, Johan A. K. Suykens +2

The success of deep learning, a brain-inspired form of AI, has sparked interest in understanding how the brain could similarly learn across multiple layers of neurons. However, the…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.